Genome-wide analysis identifies a general requirement for polarity proteins in endocytic traffic

In a genome-wide RNA-mediated interference screen for genes required in membrane traffic - including endocytic uptake, recycling from endosomes to the plasma membrane, and secretion - we identified 168 candidate endocytosis regulators and 100 candidate secretion regulators. Many of these candidates are highly conserved among metazoans but have not been previously implicated in these processes. Among the positives from the screen, we identified PAR-3, PAR-6, PKC-3 and CDC-42, proteins that are well known for their importance in the generation of embryonic and epithelial-cell polarity. Further analysis showed that endocytic transport in Caenorhabditis elegans coelomocytes and human HeLa cells was also compromised after perturbation of CDC-42/Cdc42 or PAR-6/Par6 function, indicating a general requirement for these proteins in regulating endocytic traffic. Consistent with these results, we found that tagged CDC-42/Cdc42 is enriched on recycling endosomes in C. elegans and mammalian cells, suggesting a direct function in the regulation of transport.

Mass spectrometric analysis of HOCl- and free-radical-induced damage to lipids and proteins

In inflammatory diseases, release of oxidants leads to oxidative damage to biomolecules. HOCl (hypochlorous acid), released by the myeloperoxidase/H2O2/Cl- system, can cause formation of phospholipid chlorohydrins, or alpha-chloro-fatty aldehydes from plasmalogens. It can attack several amino acid residues in proteins, causing post-translational oxidative modifications of proteins, but the formation of 3-chlorotyrosine is one of the most stable markers of HOCl-induced damage. Soft-ionization MS has proved invaluable for detecting the occurrence of oxidative modifications to both phospholipids and proteins, and characterizing the products generated by HOCl-induced attack. For both phospholipids and proteins, the application of advanced mass spectrometric methods such as product or precursor ion scanning and neutral loss analysis can yield information both about the specific nature of the oxidative modification and the biomolecule modified. The ideal is to be able to apply these methods to complex biological or clinical samples, to determine the site-specific modifications of particular cellular components. This is important for understanding disease mechanisms and offers potential for development of novel biomarkers of inflammatory diseases. In the present paper, we review some of the progress that has been made towards this goal.

Immunological and biochemical techniques in the analysis of tear proteins

This study is concerned with the analysis of tear proteins, paying particular attention to the state of the tears (e.g. non-stimulated, reflex, closed), created during sampling, and to assess their interactions with hydrogel contact lenses. The work has involved the use of a variety of biochemical and immunological analytical techniques for the measurement of proteins, (a), in tears, (b), on the contact lens, and (c), in the eluate of extracted lenses. Although a diverse range of tear components may contribute to contact lens spoilation, proteins were of particular interest in this study because of their theoretical potential for producing immunological reactions. Although normal host proteins in their natural state are generally not treated as dangerous or non-self, those which undergo denaturation or suffer a conformational change may provoke an excessive and unnecessary immune response. A novel on-lens cell based assay has been developed and exploited in order to study the role of the ubiquitous cell adhesion glycoprotein, vitronectin, in tears and contact lens wear under various parameters. Vitronectin, whose levels are known to increase in the closed eye environment and shown here to increase during contact lens wear, is an important immunoregulatory protein and may be a prominent marker of inflammatory activity. Immunodiffusion assays were developed and optimised for use in tear analysis, and in a series of subsequent studies used for example in the measurement of albumin, lactoferrin, IgA and IgG. The immunodiffusion assays were then applied in the estimation of the closed eye environment; an environment which has been described as sustaining a state of sub-clinical inflammation. The role and presence of a lesser understood and investigated protein, kininogen, was also estimated, in particular, in relation to contact lens wear. Difficulties arise when attempting to extract proteins from the contact lens in order to examine the individual nature of the proteins involved. These problems were partly alleviated with the use of the on-lens cell assay and a UV spectrophotometry assay, which can analyse the lens surface and bulk respectively, the latter yielding only total protein values. Various lens extraction methods were investigated to remove protein from the lens and the most efficient was employed in the analysis of lens extracts. Counter immunoelectrophoresis, an immunodiffusion assay, was then applied to the analysis of albumin, lactoferrin, IgA and IgG in the resultant eluates.

A proteo-liposome system for the analysis of the intracellular interactome of membrane proteins using amyloid precursor protein as a model

Transmembrane proteins play crucial roles in many important physiological processes. The intracellular domain of membrane proteins is key for their function by interacting with a wide variety of cytosolic proteins. It is therefore important to examine this interaction. A recently developed method to study these interactions, based on the use of liposomes as a model membrane, involves the covalent coupling of the cytoplasmic domains of membrane proteins to the liposome membrane. This allows for the analysis of interaction partners requiring both protein and membrane lipid binding. This thesis further establishes the liposome recruitment system and utilises it to examine the intracellular interactome of the amyloid precursor protein (APP), most well-known for its proteolytic cleavage that results in the production and accumulation of amyloid beta fragments, the main constituent of amyloid plaques in Alzheimer’s disease pathology. Despite this, the physiological function of APP remains largely unclear. Through the use of the proteo-liposome recruitment system two novel interactions of APP’s intracellular domain (AICD) are examined with a view to gaining a greater insight into APP’s physiological function. One of these novel interactions is between AICD and the mTOR complex, a serine/threonine protein kinase that integrates signals from nutrients and growth factors. The kinase domain of mTOR directly binds to AICD and the N-terminal amino acids of AICD are crucial for this interaction. The second novel interaction is between AICD and the endosomal PIKfyve complex, a lipid kinase involved in the production of phosphatidylinositol-3,5-bisphosphate (PI(3,5)P2) from phosphatidylinositol-3-phosphate, which has a role in controlling ensdosome dynamics. The scaffold protein Vac14 of the PIKfyve complex binds directly to AICD and the C-terminus of AICD is important for its interaction with the PIKfyve complex. Using a recently developed intracellular PI(3,5)P2 probe it is shown that APP controls the formation of PI(3,5)P2 positive vesicular structures and that the PIKfyve complex is involved in the trafficking and degradation of APP. Both of these novel APP interactors have important implications of both APP function and Alzheimer’s disease. The proteo-liposome recruitment method is further validated through its use to examine the recruitment and assembly of the AP-2/clathrin coat from purified components to two membrane proteins containing different sorting motifs. Taken together this thesis highlights the proteo-liposome recruitment system as a valuable tool for the study of membrane proteins intracellular interactome. It allows for the mimicking of the protein in its native configuration therefore identifying weaker interactions that are not detected by more conventional methods and also detecting interactions that are mediated by membrane phospholipids.

A systematic analysis of the role of GGDEF-EAL domain proteins in virulence and motility in Xanthomonas oryzae pv. oryzicola

The second messenger c-di-GMP is implicated in regulation of various aspects of the lifestyles and virulence of Gram-negative bacteria. Cyclic di-GMP is formed by diguanylate cyclases with a GGDEF domain and degraded by phosphodiesterases with either an EAL or HD-GYP domain. Proteins with tandem GGDEF-EAL domains occur in many bacteria, where they may be involved in c-di-GMP turnover or act as enzymatically-inactive c-di-GMP effectors. Here, we report a systematic study of the regulatory action of the eleven GGDEF-EAL proteins in Xanthomonas oryzae pv. oryzicola, an important rice pathogen causing bacterial leaf streak. Mutational analysis revealed that XOC_2335 and XOC_2393 positively regulate bacterial swimming motility, while XOC_2102, XOC_2393 and XOC_4190 negatively control sliding motility. The ΔXOC_2335/XOC_2393 mutant that had a higher intracellular c-di-GMP level than the wild type and the ΔXOC_4190 mutant exhibited reduced virulence to rice after pressure inoculation. In vitro purified XOC_4190 and XOC_2102 have little or no diguanylate cyclase or phosphodiesterase activity, which is consistent with unaltered c-di-GMP concentration in ΔXOC_4190. Nevertheless, both proteins can bind to c-di-GMP with high affinity, indicating a potential role as c-di-GMP effectors. Overall our findings advance understanding of c-di-GMP signaling and its links to virulence in an important rice pathogen.

Protein cutoff scanning: a comparative analysis of cutoff dependent and cutoff free methods for prospecting contacts in proteins.

In this study, we carried out a comparative analysis between two classical methodologies to prospect residue contacts in proteins: the traditional cutoff dependent (CD) approach and cutoff free Delaunay tessellation (DT). In addition, two alternative coarse-grained forms to represent residues were tested: using alpha carbon (CA) and side chain geometric center (GC). A database was built, comprising three top classes: all alpha, all beta, and alpha/beta. We found that the cutoff value? at about 7.0 A emerges as an important distance parameter.? Up to 7.0 A, CD and DT properties are unified, which implies that at this distance all contacts are complete and legitimate (not occluded). We also have shown that DT has an intrinsic missing edges problem when mapping the first layer of neighbors. In proteins, it may produce systematic errors affecting mainly the contact network in beta chains with CA. The almost-Delaunay (AD) approach has been proposed to solve this DT problem. We found that even AD may not be an advantageous solution. As a consequence, in the strict range up ? to 7.0 A, the CD approach revealed to be a simpler, more complete, and reliable technique than DT or AD. Finally, we have shown that coarse-grained residue representations may introduce bias in the analysis of neighbors in cutoffs up to ? 6.8 A, with CA favoring alpha proteins and GC favoring beta proteins. This provides an additional argument pointing to ? the value of 7.0 A as an important lower bound cutoff to be used in contact analysis of proteins.

Investigation of highly regulated promoters for the production of recombinant proteins in plants

Plants have been identified as promising expression systems for the commercial production of recombinant proteins. Plant-based protein production or “biofarming” offers a number of advantages over traditional expression systems in terms of scale of production, the capacity for post-translation processing, providing a product free of contaminants and cost effectiveness. A number of pharmaceutically important and commercially valuable proteins, such as antibodies, biopharmaceuticals and industrial enzymes are currently being produced in plant expression systems. However, several challenges still remain to improve recombinant protein yield with no ill effect on the host plant. The ability for transgenic plants to produce foreign proteins at commercially viable levels can be directly related to the level and cell specificity of the selected promoter driving the transgene. The accumulation of recombinant proteins may be controlled by a tissue-specific, developmentally-regulated or chemically-inducible promoter such that expression of recombinant proteins can be spatially- or temporally- controlled. The strict control of gene expression is particularly useful for proteins that are considered toxic and whose expression is likely to have a detrimental effect on plant growth. To date, the most commonly used promoter in plant biotechnology is the cauliflower mosaic virus (CaMV) 35S promoter which is used to drive strong, constitutive transgene expression in most organs of transgenic plants. Of particular interest to researchers in the Centre for Tropical Crops and Biocommodities at QUT are tissue-specific promoters for the accumulation of foreign proteins in the roots, seeds and fruit of various plant species, including tobacco, banana and sugarcane. Therefore this Masters project aimed to isolate and characterise root- and seed-specific promoters for the control of genes encoding recombinant proteins in plant-based expression systems. Additionally, the effects of matching cognate terminators with their respective gene promoters were assessed. The Arabidopsis root promoters ARSK1 and EIR1 were selected from the literature based on their reported limited root expression profiles. Both promoters were analysed using the PlantCARE database to identify putative motifs or cis-acting elements that may be associated with this activity. A number of motifs were identified in the ARSK1 promoter region including, WUN (wound-inducible), MBS (MYB binding site), Skn-1, and a RY core element (seed-specific) and in the EIR1 promoter region including, Skn-1 (seed-specific), Box-W1 (fungal elicitor), Aux-RR core (auxin response) and ABRE (ABA response). However, no previously reported root-specific cis-acting elements were observed in either promoter region. To confirm root specificity, both promoters, and truncated versions, were fused to the GUS reporter gene and the expression cassette introduced into Arabidopsis via Agrobacterium-mediated transformation. Despite the reported tissue-specific nature of these promoters, both upstream regulatory regions directed constitutive GUS expression in all transgenic plants. Further, similar levels of GUS expression from the ARSK1 promoter were directed by the control CaMV 35S promoter. The truncated version of the EIR1 promoter (1.2 Kb) showed some differences in the level of GUS expression compared to the 2.2 Kb promoter. Therefore, this suggests an enhancer element is contained in the 2.2 Kb upstream region that increases transgene expression. The Arabidopsis seed-specific genes ATS1 and ATS3 were selected from the literature based on their seed-specific expression profiles and gene expression confirmed in this study as seed-specific by RT-PCR analysis. The selected promoter regions were analysed using the PlantCARE database in order to identify any putative cis elements. The seed-specific motifs GCN4 and Skn-1 were identified in both promoter regions that are associated with elevated expression levels in the endosperm. Additionaly, the seed-specific RY element and the ABRE were located in the ATS1 promoter. Both promoters were fused to the GUS reporter gene and used to transform Arabidopsis plants. GUS expression from the putative promoters was consitutive in all transgenic Arabidopsis tissue tested. Importantly, the positive control FAE1 seed-specific promoter also directed constitutive GUS expression throughout transgenic Arabidopsis plants. The constitutive nature seen in all of the promoters used in this study was not anticipated. While variations in promoter activity can be caused by a number of influencing factors, the variation in promoter activity observed here would imply a major contributing factor common to all plant expression cassettes tested. All promoter constructs generated in this study were based on the binary vector pCAMBIA2300. This vector contains the plant selection gene (NPTII) under the transcriptional control of the duplicated CaMV 35S promoter. This CaMV 35S promoter contains two enhancer domains that confer strong, constitutive expression of the selection gene and is located immediately upstream of the promoter-GUS fusion. During the course of this project, Yoo et al. (2005) reported that transgene expression is significantly affected when the expression cassette is located on the same T-DNA as the 35S enhancer. It was concluded, the trans-acting effects of the enhancer activate and control transgene expression causing irregular expression patterns. This phenomenon seems the most plausible reason for the constitutive expression profiles observed with the root- and seed-specific promoters assessed in this study. The expression from some promoters can be influenced by their cognate terminator sequences. Therefore, the Arabidopsis ARSK1, EIR1, ATS1 and ATS3 terminator sequences were isolated and incorporated into expression cassettes containing the GUS reporter gene under the control of their cognate promoters. Again, unrestricted GUS activity was displayed throughout transgenic plants transformed with these reporter gene fusions. As previously discussed constitutive GUS expression was most likely due to the trans-acting effect of the upstream CaMV 35S promoter in the selection cassette located on the same T-DNA. The results obtained in this study make it impossible to assess the influence matching terminators with their cognate promoters have on transgene expression profiles. The obvious future direction of research continuing from this study would be to transform pBIN-based promoter-GUS fusions (ie. constructs containing no CaMV 35S promoter driving the plant selection gene) into Arabidopsis in order to determine the true tissue specificity of these promoters and evaluate the effects of their cognate 3’ terminator sequences. Further, promoter truncations based around the cis-elements identified here may assist in determining whether these motifs are in fact involved in the overall activity of the promoter.

Multiscale analysis of protein functions and stochastic modelling of gene transcriptional regulatory networks

Genomic and proteomic analyses have attracted a great deal of interests in biological research in recent years. Many methods have been applied to discover useful information contained in the enormous databases of genomic sequences and amino acid sequences. The results of these investigations inspire further research in biological fields in return. These biological sequences, which may be considered as multiscale sequences, have some specific features which need further efforts to characterise using more refined methods. This project aims to study some of these biological challenges with multiscale analysis methods and stochastic modelling approach. The first part of the thesis aims to cluster some unknown proteins, and classify their families as well as their structural classes. A development in proteomic analysis is concerned with the determination of protein functions. The first step in this development is to classify proteins and predict their families. This motives us to study some unknown proteins from specific families, and to cluster them into families and structural classes. We select a large number of proteins from the same families or superfamilies, and link them to simulate some unknown large proteins from these families. We use multifractal analysis and the wavelet method to capture the characteristics of these linked proteins. The simulation results show that the method is valid for the classification of large proteins. The second part of the thesis aims to explore the relationship of proteins based on a layered comparison with their components. Many methods are based on homology of proteins because the resemblance at the protein sequence level normally indicates the similarity of functions and structures. However, some proteins may have similar functions with low sequential identity. We consider protein sequences at detail level to investigate the problem of comparison of proteins. The comparison is based on the empirical mode decomposition (EMD), and protein sequences are detected with the intrinsic mode functions. A measure of similarity is introduced with a new cross-correlation formula. The similarity results show that the EMD is useful for detection of functional relationships of proteins. The third part of the thesis aims to investigate the transcriptional regulatory network of yeast cell cycle via stochastic differential equations. As the investigation of genome-wide gene expressions has become a focus in genomic analysis, researchers have tried to understand the mechanisms of the yeast genome for many years. How cells control gene expressions still needs further investigation. We use a stochastic differential equation to model the expression profile of a target gene. We modify the model with a Gaussian membership function. For each target gene, a transcriptional rate is obtained, and the estimated transcriptional rate is also calculated with the information from five possible transcriptional regulators. Some regulators of these target genes are verified with the related references. With these results, we construct a transcriptional regulatory network for the genes from the yeast Saccharomyces cerevisiae. The construction of transcriptional regulatory network is useful for detecting more mechanisms of the yeast cell cycle.

Prediction of cis/trans isomerization in proteins using PSI-BLAST profiles and secondary structure information

Background The majority of peptide bonds in proteins are found to occur in the trans conformation. However, for proline residues, a considerable fraction of Prolyl peptide bonds adopt the cis form. Proline cis/trans isomerization is known to play a critical role in protein folding, splicing, cell signaling and transmembrane active transport. Accurate prediction of proline cis/trans isomerization in proteins would have many important applications towards the understanding of protein structure and function. Results In this paper, we propose a new approach to predict the proline cis/trans isomerization in proteins using support vector machine (SVM). The preliminary results indicated that using Radial Basis Function (RBF) kernels could lead to better prediction performance than that of polynomial and linear kernel functions. We used single sequence information of different local window sizes, amino acid compositions of different local sequences, multiple sequence alignment obtained from PSI-BLAST and the secondary structure information predicted by PSIPRED. We explored these different sequence encoding schemes in order to investigate their effects on the prediction performance. The training and testing of this approach was performed on a newly enlarged dataset of 2424 non-homologous proteins determined by X-Ray diffraction method using 5-fold cross-validation. Selecting the window size 11 provided the best performance for determining the proline cis/trans isomerization based on the single amino acid sequence. It was found that using multiple sequence alignments in the form of PSI-BLAST profiles could significantly improve the prediction performance, the prediction accuracy increased from 62.8% with single sequence to 69.8% and Matthews Correlation Coefficient (MCC) improved from 0.26 with single local sequence to 0.40. Furthermore, if coupled with the predicted secondary structure information by PSIPRED, our method yielded a prediction accuracy of 71.5% and MCC of 0.43, 9% and 0.17 higher than the accuracy achieved based on the singe sequence information, respectively. Conclusion A new method has been developed to predict the proline cis/trans isomerization in proteins based on support vector machine, which used the single amino acid sequence with different local window sizes, the amino acid compositions of local sequence flanking centered proline residues, the position-specific scoring matrices (PSSMs) extracted by PSI-BLAST and the predicted secondary structures generated by PSIPRED. The successful application of SVM approach in this study reinforced that SVM is a powerful tool in predicting proline cis/trans isomerization in proteins and biological sequence analysis.

Massively parallel sequencing and analysis of expressed sequence tags in a successful invasive plant

Background Invasive species pose a significant threat to global economies, agriculture and biodiversity. Despite progress towards understanding the ecological factors associated with plant invasions, limited genomic resources have made it difficult to elucidate the evolutionary and genetic factors responsible for invasiveness. This study presents the first expressed sequence tag (EST) collection for Senecio madagascariensis, a globally invasive plant species. Methods We used pyrosequencing of one normalized and two subtractive libraries, derived from one native and one invasive population, to generate an EST collection. ESTs were assembled into contigs, annotated by BLAST comparison with the NCBI non-redundant protein database and assigned gene ontology (GO) terms from the Plant GO Slim ontologies. Key Results Assembly of the 221 746 sequence reads resulted in 12 442 contigs. Over 50 % (6183) of 12 442 contigs showed significant homology to proteins in the NCBI database, representing approx. 4800 independent transcripts. The molecular transducer GO term was significantly over-represented in the native (South African) subtractive library compared with the invasive (Australian) library. Based on NCBI BLAST hits and literature searches, 40 % of the molecular transducer genes identified in the South African subtractive library are likely to be involved in response to biotic stimuli, such as fungal, bacterial and viral pathogens. Conclusions This EST collection is the first representation of the S. madagascariensis transcriptome and provides an important resource for the discovery of candidate genes associated with plant invasiveness. The over-representation of molecular transducer genes associated with defence responses in the native subtractive library provides preliminary support for aspects of the enemy release and evolution of increased competitive ability hypotheses in this successful invasive. This study highlights the contribution of next-generation sequencing to better understanding the molecular mechanisms underlying ecological hypotheses that are important in successful plant invasions.

Fuzzy methods for analysis of microarrays and networks

Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) clustering of microarrays; (2) identification of disease-associated genes in microarrays; and (3) identification of protein complexes in PPI networks. The first part of the thesis aims to detect, by the fuzzy C-means (FCM) method, clustering structures in DNA microarrays corrupted by noise. Because of the presence of noise, some clustering structures found in random data may not have any biological significance. In this part, we propose to combine the FCM with the empirical mode decomposition (EMD) for clustering microarray data. The purpose of EMD is to reduce, preferably to remove, the effect of noise, resulting in what is known as denoised data. We call this method the fuzzy C-means method with empirical mode decomposition (FCM-EMD). We applied this method on yeast and serum microarrays, and the silhouette values are used for assessment of the quality of clustering. The results indicate that the clustering structures of denoised data are more reasonable, implying that genes have tighter association with their clusters. Furthermore we found that the estimation of the fuzzy parameter m, which is a difficult step, can be avoided to some extent by analysing denoised microarray data. The second part aims to identify disease-associated genes from DNA microarray data which are generated under different conditions, e.g., patients and normal people. We developed a type-2 fuzzy membership (FM) function for identification of diseaseassociated genes. This approach is applied to diabetes and lung cancer data, and a comparison with the original FM test was carried out. Among the ten best-ranked genes of diabetes identified by the type-2 FM test, seven genes have been confirmed as diabetes-associated genes according to gene description information in Gene Bank and the published literature. An additional gene is further identified. Among the ten best-ranked genes identified in lung cancer data, seven are confirmed that they are associated with lung cancer or its treatment. The type-2 FM-d values are significantly different, which makes the identifications more convincing than the original FM test. The third part of the thesis aims to identify protein complexes in large interaction networks. Identification of protein complexes is crucial to understand the principles of cellular organisation and to predict protein functions. In this part, we proposed a novel method which combines the fuzzy clustering method and interaction probability to identify the overlapping and non-overlapping community structures in PPI networks, then to detect protein complexes in these sub-networks. Our method is based on both the fuzzy relation model and the graph model. We applied the method on several PPI networks and compared with a popular protein complex identification method, the clique percolation method. For the same data, we detected more protein complexes. We also applied our method on two social networks. The results showed our method works well for detecting sub-networks and give a reasonable understanding of these communities.

Prognostic significance of IGF and ECM induced signalling proteins in breast cancer patients

Breast cancer is a leading contributor to the burden of disease in Australia. Fortunately, the recent introduction of diverse therapeutic strategies have improved the survival outcome for many women. Despite this, the clinical management of breast cancer remains problematic as not all approaches are sufficiently sophisticated to take into account the heterogeneity of this disease and are unable to predict disease progression, in particular, metastasis. As such, women with good prognostic outcomes are exposed to the side effects of therapies without added benefit. Furthermore, women with aggressive disease for whom these advanced treatments would deliver benefit cannot be distinguished and opportunities for more intensive or novel treatment are lost. This study is designed to identify novel factors associated with disease progression, and the potential to inform disease prognosis. Frequently overlooked, yet common mediators of disease are the interactions that take place between the insulin-like growth factor (IGF) system and the extracellular matrix (ECM). Our laboratory has previously demonstrated that multiprotein insulin-like growth factor-I (IGF-I): insulin-like growth factor binding protein (IGFBP): vitronectin (VN) complexes stimulate migration of breast cancer cells in vitro, via the cooperative involvement of the insulin-like growth factor type I receptor (IGF-IR) and VN-binding integrins. However, the effects of IGF and ECM protein interactions on the dissemination and progression of breast cancer in vivo are unknown. It was hypothesised that interactions between proteins required for IGF induced signalling events and those within the ECM contribute to breast cancer metastasis and are prognostic and predictive indicators of patient outcome. To address this hypothesis, semiquantitative immunohistochemistry (IHC) analyses were performed to compare the extracellular and subcellular distribution of IGF and ECM induced signalling proteins between matched normal, primary cancer, and metastatic cancer among archival formalin-fixed paraffin-embedded (FFPE) breast tissue samples collected from women attending the Princess Alexandra Hospital, Brisbane. Multivariate Cox proportional hazards (PH) regression survival models in conjunction with a modified „purposeful selection of covariates. method were applied to determine the prognostic potential of these proteins. This study provides the first in-depth, compartmentalised analysis of the distribution of IGF and ECM induced signalling proteins. As protein function and protein localisation are closely correlated, these findings provide novel insights into IGF signalling and ECM protein function during breast cancer development and progression. Distinct IGF signalling and ECM protein immunoreactivity was observed in the stroma and/or in subcellular locations in normal breast, primary cancer and metastatic cancer tissues. Analysis of the presence and location of stratifin (SFN) suggested a causal relationship in ECM remodelling events during breast cancer development and progression. The results of this study have also suggested that fibronectin (FN) and ¥â1 integrin are important for the formation of invadopodia and epithelial-to-mesenchymal transition (EMT) events. Our data also highlighted the importance of the temporal and spatial distribution of IGF induced signalling proteins in breast cancer metastasis; in particular, SFN, enhancer-of-split and hairy-related protein 2 (SHARP-2), total-akt/protein kinase B 1 (Total-AKT1), phosphorylated-akt/protein kinase B (P-AKT), extracellular signal-related kinase-1 and extracellular signal-related kinase-2 (ERK1/2) and phosphorylated-extracellular signal-related kinase-1 and extracellular signal-related kinase-2 (P-ERK1/2). Multivariate survival models were created from the immunohistochemical data. These models were found to fit well with these data with very high statistical confidence. Numerous prognostic confounding effects and effect modifications were identified among elements of the ECM and IGF signalling cascade and corroborate the survival models. This finding provides further evidence for the prognostic potential of IGF and ECM induced signalling proteins. In addition, the adjusted measures of associations obtained in this study have strengthened the validity and utility of the resulting models. The findings from this study provide insights into the biological interactions that occur during the development of breast tissue and contribute to disease progression. Importantly, these multivariate survival models could provide important prognostic and predictive indicators that assist the clinical management of breast disease, namely in the early identification of cancers with a propensity to metastasise, and/or recur following adjuvant therapy. The outcomes of this study further inform the development of new therapeutics to aid patient recovery. The findings from this study have widespread clinical application in the diagnosis of disease and prognosis of disease progression, and inform the most appropriate clinical management of individuals with breast cancer.